Description: 本程序包是关于图形处理和人脸识别的,包括人脸Gabor特征提取，canny算子，水线阈值方法等．大家可以一起参考-The package is on the graphics processing and face recognition, including face Gabor feature extraction, canny operator, waterline threshold methods. Together we can make reference Platform: |
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Author:单昊 |
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Description: 利用Sub-pattern PCA在Yale人脸库上进行人脸识别的matlab源代码，子模式主成分分析首先对原始图像分块，然后对相同位置的子图像分别建立子图像集，在每一个子图像集内使用PCA方法提取特征，建立子空间。对待识别图像，经相同分块后，分别将子图像向对应的子空间投影，提取特征。最后根据最近邻原则进行分类。-Sub-pattern PCA use in the Yale face database for face recognition on the matlab source code, sub-mode principal component analysis first of the original image block, and then the same sub-image, respectively, the location of the establishment of sub-image set, in each sub-image Set the use of PCA to extract the features, the establishment of sub-space. Treatment to identify images, by the same block, the respective sub-image to the corresponding sub-space projection, feature extraction. Finally, according to the principle of nearest neighbor classification. Platform: |
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Author:章格 |
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Description: pca人脸特征提取，可以根据需要提取不同维数的特征脸。-pca facial feature extraction, can extract the characteristics of the different dimensions of the face. Platform: |
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Author:胡欢欢 |
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Description: 为了更有效地提取图像的局部特征，提出了一种基于2维偏最小二乘法(two—dimensional partial least
square，2DPLS)的图像局部特征提取方法，并将其应用于面部表情识别中。该方法首先利用局部二元模式(1ocal
binary pattern，LBP)算子提取一幅图像中所有子块的纹理特征，并将其组合成局部纹理特征矩阵。由于样本图像
被转化为局部纹理特征矩阵，因此可将传统PLS方法推广为2DPLS方法，用来提取其中的判别信息。2DPLS方法
通过对类成员关系矩阵的构造进行相应的修改，使其适应样本的矩阵形式，并能体现出人脸局部信息重要性的差
异。同时，对于类成员关系协方差矩阵的奇异性问题，也推导出了其广义逆的解析解。基于JAFFE人脸表情库的
实验结果表明，该方法不但可以有效地提取图像局部特征，并能取得良好的表情识别效果。-To better the image of the local feature extraction, a partial least squares method based on 2D (two-dimensional partial least
square, 2DPLS) image local feature extraction method, and applied to facial expression recognition. In this method, use of local binary pattern (1ocal
binary pattern, LBP) operator extracts an image texture features of all sub-blocks, and their combination into the local texture feature matrix. As the sample image
Be translated into the local texture feature matrix, so the traditional PLS method can be generalized to 2DPLS method used to extract the identification information. 2DPLS method
Through the class membership matrix in the corresponding modifications to adapt the sample matrix, and can reflect the importance of face poor local information
Different. Meanwhile, members of the class covariance matrix of the singular relations issues, also derived the generalized inverse of the analytical solution. Based on the JAFFE facial expression database
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Author:MJ |
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Description: 计算机人脸识别技术( Face Reocgnition)就利用计算机分析人脸图像,从中提取出有效的识别信息,用来辨认身份的一门技术。[ 1 ]即对已知人脸进行标准化处理后,通过某种方法和数据库中的人脸样本进行匹配,寻找库中对应人脸及该人脸相关信息。人脸自动识别系统有两个主要技术环节,一是人脸定位,即从输入图像中找到人脸存在的位置,将人脸从背景中分割出来,二是对标准化后的人脸图像进行特征提取和识别。本文中介绍的PCA (特征脸)方法就是一种常用的人脸
特征提取方法。-Computer Face Recognition Technology (Face Reocgnition) on the use of computer analysis of facial image, to extract the valid identification information used to identify the status of a technology. [1] that is known to standardize treatment of face, through a method and a database of face samples for matching, search library, the corresponding face and the face-related information. Automatic face recognition system has two main technical aspects, first, face location, that is, from the input image to find the location of the face there, the faces will be split out from the background, the second is, the standard features of face images extraction and recognition. Described in this paper PCA (Eigenfaces) method is a common facial feature extraction method. Platform: |
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Author:Highjoe |
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Description: pca又称主成分分析，主要用来提取图像的主要成分，作为特征提取一个重要算法，将其用于人脸识别-pca, also known as principal component analysis, mainly used to extract the main component of the image, as a key feature extraction algorithm, be used in face recognition Platform: |
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Author:DD |
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Description: 本课题研究的步骤如下：先提取人脸的特征向量；产生训练样本和测试样本；再用LVQ创建神经网络模型，该模型用训练样本进行训练调整权值；用测试样本对建立的人脸朝向识别模型进行验证，要求有较高的识别率。
本课题要求使用LVQ神经网络的算法进行Matlab仿真，对人脸朝向进行有效的判断和识别。
-This study is the following steps: first extract facial feature vector generate training and testing samples reuse create LVQ neural network model, which is trained using training samples to adjust the weights using the test sample towards the establishment of a human face recognition model validated requires a higher recognition rate. This topic requires the use of LVQ neural network algorithm Matlab simulation, the human face towards effective judgment and identification. Platform: |
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Author:吴军 |
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Description: PIVlab - 时间分辨粒子图像测速（PIV）工具：
一种基于GUI的工具，用于预处理，分析，验证，后处理，可视化和模拟PIV数据。
使用MATLAB网络研讨会进行人脸识别代码：
使用MATLAB在线讲座的人脸识别中的主要演示文件。
Gabor特征提取：
该程序生成一个自定义Gabor滤波器组; 并使用它们提取图像特征。
主成分分析：
用于特征提取；
链码：
基于MATLAB的freeman的曲面轮廓描述(PIVlab - time resolved particle image velocimetry (PIV) tool:
A GUI based tool for preprocessing, analysis, validation, post processing, visualization, and Simulation of PIV data.
Using MATLAB webinar for face recognition code:
The main demo file is used in MATLAB online lectures for face recognition.
Gabor feature extraction:
The program generates a custom Gabor filter bank and uses them to extract image features.
Principal component analysis:
For feature extraction;
Chain code:
Surface contour description of Freeman based on MATLAB) Platform: |
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Author:long1219
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Description: 利用积分图的方式提取图像hog特征，用于人脸、行人检测。(Using the integral plot to extract the image hog feature, for human face, pedestrian detection.) Platform: |
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Author:cqzj_jia
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Search - Feature Extract face matlab